ArticleBritish journal of sports medicine2021
Reallocation of time between device-measured movement behaviours and risk of incident cardiovascular disease.
Article in British journal of sports medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 138 papers, 1 of them a synthesis that pooled it.
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Who cites it
138 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Characterizing device-measured sleep in observational health research using compositional data analysis: a systematic review.The international journal of behavioral nutrition and physical activity · 2026Pooled it
- Age-Specific Associations of Moderate-to-Vigorous Physical Activity With Relative and Absolute Risk of Type 2 Diabetes in UK Biobank Participants.Diabetes, obesity & metabolism · 2026Article
- Associations of individual exposure to particulate matter with next-day physical activity and sedentary behaviour in older adults: a micro-longitudinal study.medRxiv : the preprint server for health sciences · 2026Article
- Accelerometer-derived real-world sleep stages and risk of incident diseases: A UK Biobank cohort study and phenome-wide association analysis.PLoS medicine · 2026Article
- Weekend Warrior Physical Activity, Sedentary Behavior, and Incident Disability in Middle-Aged and Older Adults: A UK Biobank Accelerometer Study.Geriatrics & gerontology international · 2026Article
- Social jet lag is associated with incident cardiovascular disease independent of sleep duration and cardiac genetic risk.Journal of internal medicine · 2026Article
- Causal Associations Between Sedentary Time and Sleep Traits.Brain and behavior · 2026Article
- 24h movement behaviours in university students compared to working age and older adults: wearable-based evidence and cardiometabolic health implications.BMC medicine · 2026Article
- Unlocking the potential of light-intensity physical activity for public health: a call to action for research.British journal of sports medicine · 2026Article
- Joint non-linear dose-response associations of device-measured physical activity and cardiorespiratory fitness with cardiovascular disease: a cohort and Mendelian randomisation study.British journal of sports medicine · 2026Article
- Prospective Physical Activity, Sitting and Sleep consortium (ProPASS): addressing methodological and geographical barriers to inform global public health guidelines, interventions and precision medicine.British journal of sports medicine · 2026Article
- Transition dynamics modeling of pre-trained accelerometry representations for time to diagnosis of Parkinson's disease.Lifetime data analysis · 2026Article
- Wearable Movement-Tracking for Prodromal Parkinson's Disease Detection: A Cross-Country Validation Study.Movement disorders : official journal of the Movement Disorder Society · 2026Article
- Interrelations of work with health and wellbeing on a 50+ year old workforce assessed using longitudinal self-reports and actigraphy.Scientific reports · 2026Article
- Association of wearableZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026Article
- A neural signature of sleep deprivation in the human brain.Nature communications · 2026Article
- Associations of Accelerometer-Derived "Weekend Warrior" Physical Activity Pattern With Incident First Cardiometabolic Disease and Cardiometabolic Multimorbidity in Individuals With Hypertension.Journal of the American Heart Association · 2026Article
- Accelerometer-Derived "Weekend Warrior" Physical Activity Pattern and Venous Thromboembolism Incidence and Mortality: A Prospective Cohort Study.Journal of the American Heart Association · 2026Article
- Sustained Reduction in Cardiopulmonary Fitness in Long COVID: A Report from the RECOVER-adult Cohort Study.JACC. Advances · 2026Article
- Accelerometer-measured postoperative physical activity confers a significant mortality benefit following joint arthroplasty.Bone & joint research · 2026Article
78 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
objectiveTo improve classification of movement behaviours in free-living accelerometer data using machine-learning methods, and to investigate the association between machine-learned movement behaviours and risk of incident cardiovascular disease (CVD) in adults.
methodsUsing free-living data from 152 participants, we developed a machine-learning model to classify movement behaviours (moderate-to-vigorous physical activity behaviours (MVPA), light physical activity behaviours, sedentary behaviour, sleep) in wrist-worn accelerometer data. Participants in UK Biobank, a prospective cohort, were asked to wear an accelerometer for 7 days, and we applied our machine-learning model to classify their movement behaviours. Using compositional data analysis Cox regression, we investigated how reallocating time between movement behaviours was associated with CVD incidence.
resultsIn leave-one-participant-out analysis, our machine-learning method classified free-living movement behaviours with mean accuracy 88% (95% CI 87% to 89%) and Cohen's kappa 0.80 (95% CI 0.79 to 0.82). Among 87 498 UK Biobank participants, there were 4105 incident CVD events. Reallocating time from any behaviour to MVPA, or reallocating time from sedentary behaviour to any behaviour, was associated with lower CVD risk. For an average individual, reallocating 20 min/day to MVPA from all other behaviours proportionally was associated with 9% (95% CI 7% to 10%) lower risk, while reallocating 1 hour/day to sedentary behaviour from all other behaviours proportionally was associated with 5% (95% CI 3% to 7%) higher risk.
conclusionMachine-learning methods classified movement behaviours accurately in free-living accelerometer data. Reallocating time from other behaviours to MVPA, and from sedentary behaviour to other behaviours, was associated with lower risk of incident CVD, and should be promoted by interventions and guidelines.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.